Author: Kadence
Last Update: 2026/04/19
Introduction
Standard Amazon reports only show you a keyword if someone clicked it. This model is different—it’s exposure-based.
It captures every search term that caused your ad to appear on a shopper's screen, even if they didn't click immediately. If a shopper searches for three different things before finally buying, this model credits all three terms. This gives you the full picture of the "search journey" that leads to your brand.
Use this data to answer:
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What terms are people searching that put my brand in front of them?
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Which broad keywords act as the "entry point" before a shopper switches to a branded search?
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How does my conversion rate change for the same keyword when it's at the "Top of Search" vs. other placements?
When to Use This Report
Pull this report when you need to look beyond simple clicks and understand the true intent of your shoppers:
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Map the "Research" Phase: Shoppers usually start broad (e.g., "Running Shoes") and end specific (e.g., "Brand X Size 10"). AMC shows you those broad terms that started the journey so you can own the category early.
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Optimize Bids by Placement: We link search terms to specific ad placements. You can finally see which keywords actually deserve a high "Top of Search" bid multiplier based on real conversion data.
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Identify "High-Visibility" Terms: Find keywords where your ads are getting high impressions but low clicks. This helps you identify where your creative or price point might not be resonating compared to the search intent.
How to Use It
The dashboard is split into two main analytical modules to help you visualize performance and discover related terms.
1. The Performance Bubble Chart This section visualizes your top-performing search terms.
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The Visuals: The size of the bubble represents search volume. Terms closer to the top-right corner indicate the best overall performance.
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The Table: Below the chart, use custom columns to pull in exclusive AMC metrics like Add to Cart (ATC), Detail Page Views (DPV), and Subscribe & Save (SnS) metrics to see exactly how a keyword drives funnel progression.

2. Related Search (The Word Cloud) This module analyzes "consecutive search behavior"—showing you the other terms a shopper types into the search bar during the same day they saw your ad.
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Discover Category Overlap: If you sell Vitamin D3, use this to see what other supplements your customers are interested in. You might find that your D3 shoppers are also searching for "Magnesium" or "Vitamin K2," signaling a perfect opportunity for a new bundle or a cross-sell campaign.
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Identify Direct Competitors: By filtering for your brand name, you can see which specific competitor brands shoppers are searching for immediately after seeing your products. This tells you exactly who you are being compared to in real-time.
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How to use it: Enter a core term (like your brand or a main product) in the filter. The word cloud will visualize the most common related terms. The larger the word, the more shoppers are searching for it alongside your primary term.

Strategic Scenarios
| Goal | What to Look For | Strategic Action |
| Bidding Optimization | Keywords with high UV but low sales at specific placements. | Lower bid multipliers for placements where a keyword is "visible" but not converting. |
| Competitor Conquesting | Your brand name in the filter, competitor names in the "Related Search" cloud. | Identify which competitors are most frequently compared to you and target their top terms. |
| Subscription Growth | Search terms with a high SnS UV. | Move budget toward keywords that drive long-term subscribers, not just one-time buyers. |
Glossary
| Type | Term | Description |
| Dimension | Search Term | Content entered by Amazon users in the search box |
| Targeting | Keywords, ASIN, or product categories targeted in ad settings | |
| Match Type | Matching rules of targeting in ad settings | |
| Placement | Ad placements in different positions on Amazon | |
| Related Search | Search terms a user searches simultaneously | |
| Metrics | UV | Unique Viewer |
| Impressions | Number of impression events | |
| Search UV | Deduplicated number of searched users | |
| Total Correlation UV | Number of users who searched both search terms | |
| Click-throughs | Number of click events | |
| Click-throughs UV | Deduplicated number of click users | |
| Total DPV | Number of detailed page view events | |
| Total DPV UV | Deduplicated number of detailed page view users | |
| Total ATC | Number of add-to-cart events | |
| Total ATC UV | Deduplicated number of add-to-cart users | |
| Total Purchase | Total Purchase | |
| Total Purchase UV | Deduplicated number of purchase users | |
| Total NTB Purchase | Total New-to-Brand Purchase | |
| Total NTB Purchase UV | Deduplicated number of new-to-brand purchase users | |
| Total Product Sales | Total revenue from product sales | |
| Total NTB Product Sales | Total revenue from new-to-brand product sales | |
| CTR | Click-through Rate (total_click/total_impression) | |
| CTR UV | Unique Click-through Rate (total_click_uv/impression_uv) | |
| Total DPVR | Detailed Page View Rate (total_dpv/total_impression) | |
| Total DPVR UV | Unique Detailed Page View Rate (dpv_uv/impression_uv) | |
| Total ATCR | Add-to-Cart Rate (total_atc/total_impression) | |
| Total ATCR UV | Unique Add-to-Cart Rate (atc_uv/impression_uv) | |
| Total NTB PR | New-to-Brand Purchase Rate (total_purchase_ntb/total_impression) | |
| Total NTB PR UV | Unique New-to-Brand Purchase Rate (purchase_uv_ntb/impression_uv) | |
| Total PR | Purchase Rate (total_purchase/total_impression) | |
| Total PR UV | Unique Viewer Purchase Rate (purchase_uv/impression_uv) | |
| Total ATV | Average Transaction Value (total_product_sales/purchase_uv) |